文章基本信息

标题：Worst-case control energy of single-input network systems
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作者：Giacomo Baggio ; Sandro Zampieri
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：13
页码：55-60
DOI：10.1016/j.ifacol.2022.07.235
语种：English
出版社：Elsevier
摘要：AbstractThe controllability of large-scale network systems has been extensively investigated in the past few years. In spite of the recent advances in this field, there are still a number of unsolved problems which are of critical importance to fully understand the practical limitations arising in the control of large-scale networks. These include the derivation of informative bounds and scaling laws for the control energy of networks controlled by a limited number of nodes. In this paper, we aim to fill this gap by establishing new numerically reliable bounds and asymptotic estimates on the worst-case control energy of continuous-time linear network systems controlled by a single node. Our results rely on a convenient reformulation of the controllability Gramian of a single-input linear system in terms of a Cauchy matrix. We illustrate and validate our theoretical findings through several examples, ranging from structured networks to random ones.
关键词：KeywordsNetwork systemscontrollabilitycontrol energycontrollability Gramian